@article{Spahr:18,
author = {Hendrik Spahr, Clara Pfäffle, Peter Koch, Helge Sudkamp, Gereon Hüttmann und Dierck Hillmann},
journal = {Opt. Express},
keywords = {Funktion, Fullfield},
number = {15},
pages = {18803--18816},
publisher = {OSA},
title = {Interferometric detection of 3D motion using computational subapertures in optical coherence tomography},
volume = {26},
month = {Jul},
year = {2018},
url = {http://www.opticsexpress.org/abstract.cfm?URI=oe-26-15-18803},
doi = {10.1364/OE.26.018803},
abstract = {Doppler optical coherence tomography (OCT) quantifies axial motion with high precision, whereas lateral motion cannot be detected by a mere evaluation of phase changes. This problem was solved by the introduction of three-beam Doppler OCT, which, however, entails a high experimental effort. Here, we present the numerical analogue to this experimental approach. Phase-stable complex-valued OCT datasets, recorded with full-field swept-source OCT, are filtered in the Fourier domain to limit imaging to different computational subapertures. These are used to calculate all three components of the motion vector with interferometric precision. As known from conventional Doppler OCT for axial motion only, the achievable accuracy exceeds the actual imaging resolution by orders of magnitude in all three dimensions. The feasibility of this method is first demonstrated by quantifying micro-rotation of a scattering sample. Subsequently, a potential application is explored by recording the 3D motion vector field of tissue during laser photocoagulation in ex-vivo porcine retina.},
}

2017

Gianni Borghesan and Mouloud Ourak and Eva Lankenau and Richard Neffin and Peter Koch and Hinnerk Schulz-Hildebrandt and Koen Willekens and Peter Stalmans and Dominiek Reynaerts and Emmanuel Vander Poorten:
Probabilistic Principal Component Analysis and Particle Filtering for real-time retina detection from a single-fiber OCT.
in Proceedings of the 7th Joint Workshop on New Technologies for Computer/Robot Assisted Surgery,
2017

@conference{Borghesan2017,
title = {Probabilistic Principal Component Analysis and Particle Filtering for real-time retina detection from a single-fiber OCT},
author = {Gianni Borghesan and Mouloud Ourak and Eva Lankenau and Richard Neffin and Peter Koch and Hinnerk Schulz-Hildebrandt and Koen Willekens and Peter Stalmans and Dominiek Reynaerts and Emmanuel Vander Poorten},
year = {2017},
date = {2017-06-02},
booktitle = {Proceedings of the 7th Joint Workshop on New Technologies for Computer/Robot Assisted Surgery},
abstract = {Vitreo-retinal surgery concerns a set of particularly demanding micro-surgical interventions that take place at the back of the eye. Examples of such procedures are retinal vein cannulation (where the surgeon aims to insert a needle in a vein of the size of human hairs) and epiretinal membrane peeling (where a detached membrane must be removed from the retina). As severe retinal damage can be caused by undesired collisions, good instrument to retina distance perception would be very useful. We propose to use an OCT-fiber instrumented tool, and purposefully designed algorithms to interpret the measurements and extract a reliable real-time distance estimate. This abstract describes the progress that was made and includes a test conducted with a robotic platform on a synthetic eye mockup.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}